def StitchPatches(hdf5_file_path, downscale=16, draw_grid=False, bg_color=(0,0,0), alpha=-1):
file = h5py.File(hdf5_file_path, 'r')
dset = file['imgs']
coords = file['coords'][:]
if 'downsampled_level_dim' in dset.attrs.keys():
w, h = dset.attrs['downsampled_level_dim']
else:
w, h = dset.attrs['level_dim']
print('original size: {} x {}'.format(w, h))
w = w // downscale
h = h //downscale
coords = (coords / downscale).astype(np.int32)
print('downscaled size for stiching: {} x {}'.format(w, h))
print('number of patches: {}'.format(len(dset)))
img_shape = dset[0].shape
print('patch shape: {}'.format(img_shape))
downscaled_shape = (img_shape[1] // downscale, img_shape[0] // downscale)
if w*h > Image.MAX_IMAGE_PIXELS:
raise Image.DecompressionBombError("Visualization Downscale %d is too large" % downscale)
if alpha < 0 or alpha == -1:
heatmap = Image.new(size=(w,h), mode="RGB", color=bg_color)
else:
heatmap = Image.new(size=(w,h), mode="RGBA", color=bg_color + (int(255 * alpha),))
heatmap = np.array(heatmap)
heatmap = DrawMap(heatmap, dset, coords, downscaled_shape, indices=None, draw_grid=draw_grid)
file.close()
return heatmap
def StitchPatches(hdf5_file_path,
pred_path,
downscale=4,
draw_grid=False,
bg_color=(0, 0, 0),
alpha=-1):
file = h5py.File(hdf5_file_path, 'r')
files = []
dset = file['imgs']
print(len(dset))
start_dir = pred_path
pattern = "*.png"
for dir, _, _ in os.walk(start_dir):
files.extend(glob(os.path.join(dir, pattern)))
print(len(files))
files.sort(key=lambda f: int(re.sub('\D', '', f)))
images = ones((len(files), 512, 512, 3))
for i, load in enumerate(files):
print(load)
images[i] = (load_image(load))
print(images[0].dtype)
#dset=files
coords = file['coords'][:]
if 'downsampled_level_dim' in dset.attrs.keys():
w, h = dset.attrs['downsampled_level_dim']
else:
w, h = dset.attrs['level_dim']
print('original size: {} x {}'.format(w, h))
w = w // downscale
h = h // downscale
coords = (coords / downscale).astype(np.int32)
print('downscaled size for stiching: {} x {}'.format(w, h))
print('number of patches: {}'.format(len(dset)))
img_shape = dset[0].shape
print('patch shape: {}'.format(img_shape))
downscaled_shape = (img_shape[1] // downscale, img_shape[0] // downscale)
if w * h > Image.MAX_IMAGE_PIXELS:
raise Image.DecompressionBombError(
"Visualization Downscale %d is too large" % downscale)
if alpha < 0 or alpha == -1:
heatmap = Image.new(size=(w, h), mode="RGB", color=bg_color)
else:
heatmap = Image.new(size=(w, h),
mode="RGBA",
color=bg_color + (int(255 * alpha), ))
heatmap = np.array(heatmap)
heatmap = DrawMap(heatmap,
images,
coords,
downscaled_shape,
indices=None,
draw_grid=draw_grid)
file.close()
return heatmap
def test_convert2png_large_image_file_security_error(self, mk_open):
mk_open.side_effect = Image.DecompressionBombError("ERROR!")
text_file_path = os.path.join(self.extracted_package, "file.txt")
web_image_generator = utils.WebImageGenerator("file.txt",
self.extracted_package)
with self.assertRaises(exceptions.WebImageGeneratorError) as exc_info:
web_image_generator.convert2png()
self.assertIn("Error opening image file ", str(exc_info.exception))
self.assertIn("file.txt", str(exc_info.exception))
def test__get_image_object_large_image_file_security_error(
self, mk_img_parser_feed):
mk_img_parser_feed.side_effect = Image.DecompressionBombError("ERROR!")
mocked_image_io = io.BytesIO()
mocked_image = Image.new("RGB", (10, 10))
mocked_image.save(mocked_image_io, "TIFF")
web_image_generator = utils.WebImageGenerator("image_tiff_2.tiff", ".")
with self.assertRaises(exceptions.WebImageGeneratorError) as exc_info:
web_image_generator._get_image_object(mocked_image_io.getvalue())
self.assertEqual(
str(exc_info.exception),
'Error reading image "image_tiff_2.tiff": ERROR!',
)
def StitchCoords(hdf5_file_path,
wsi_object,
downscale=16,
draw_grid=False,
bg_color=(0, 0, 0),
alpha=-1):
wsi = wsi_object.getOpenSlide()
vis_level = wsi.get_best_level_for_downsample(downscale)
file = h5py.File(hdf5_file_path, 'r')
dset = file['coords']
coords = dset[:]
w, h = wsi.level_dimensions[0]
print('start stitching {}'.format(dset.attrs['name']))
print('original size: {} x {}'.format(w, h))
w, h = wsi.level_dimensions[vis_level]
print('downscaled size for stiching: {} x {}'.format(w, h))
print('number of patches: {}'.format(len(coords)))
patch_size = dset.attrs['patch_size']
patch_level = dset.attrs['patch_level']
print('patch size: {}x{} patch level: {}'.format(patch_size, patch_size,
patch_level))
patch_size = tuple((np.array((patch_size, patch_size)) *
wsi.level_downsamples[patch_level]).astype(np.int32))
print('ref patch size: {}x{}'.format(patch_size, patch_size))
if w * h > Image.MAX_IMAGE_PIXELS:
raise Image.DecompressionBombError(
"Visualization Downscale %d is too large" % downscale)
if alpha < 0 or alpha == -1:
heatmap = Image.new(size=(w, h), mode="RGB", color=bg_color)
else:
heatmap = Image.new(size=(w, h),
mode="RGBA",
color=bg_color + (int(255 * alpha), ))
heatmap = np.array(heatmap)
heatmap = DrawMapFromCoords(heatmap,
wsi_object,
coords,
patch_size,
vis_level,
indices=None,
draw_grid=draw_grid)
file.close()
return heatmap
def test_create_thumbnail_large_image_file_security_error(self, mk_open):
mk_open.side_effect = Image.DecompressionBombError("ERROR!")
text_file_path = os.path.join(self.extracted_package, "file.txt")
with open(text_file_path, "w") as fp:
fp.write("Text file content.")
web_image_generator = utils.WebImageGenerator("file.txt",
self.extracted_package)
with self.assertRaises(exceptions.WebImageGeneratorError) as exc_info:
web_image_generator.create_thumbnail()
self.assertIn("Error opening image file ", str(exc_info.exception))
self.assertIn("file.txt", str(exc_info.exception))
self.assertFalse(
os.path.exists(os.path.join(self.extracted_package, "file.png")))
def test_get_image_from_url_decompression_bomb(mocker):
session_mock = mocker.Mock()
response_mock = mocker.Mock()
mocker.patch("robotoff.utils.Image",
**{"open.side_effect": Image.DecompressionBombError()})
response_mock.content = generate_image()
response_mock.ok = True
response_mock.status_code = 200
session_mock.get.return_value = response_mock
with pytest.raises(ImageLoadingException,
match="Decompression bomb error for image MOCK_URL"):
get_image_from_url("MOCK_URL", error_raise=True, session=session_mock)
image = get_image_from_url("MOCK_URL",
error_raise=False,
session=session_mock)
assert image is None
